Python Ecosystem (Perfect for intermediate). Specifically pandas and scikit-learn on top of the SciPy platform. You can use the same code and models in development and they are reliable enough to run in operations.

R Platform (Perfect for advanced). R was designed for statistical computing, and although the language is arcane and some of the packages are poorly documented, it offers the most methods as well as state of the art techniques.

Keras for Deep Learning. It uses Python meaning you can leverage the whole Python ecosystem which saves a lot of time. The interface is very clean, whilst also supporting the power of the Theano and Keras back-ends.

I am a research student, Im working on ML using MATLAB, any advice on how to learn good programming skills in MATLAB? Im completely new to this field..I am trying to make a hybrid model with an optimization algorithm and ML. I have codes for both but dont know how to go further.
Thanks in advance.

Great site and great resources. I purchased the machine learning mastery with R and it really does help with the concepts. Especially towards the end when I do the projects from beginning to end, does it really then come together.

I did want to ask this though: do you have any suggestions about the next logical step, which is translating the data to a business person(I,e, your boss, who is not a machine learner)?

Suppose I go through the entire process, find a good algorithm that works on my test data, and run it against a ‘truly live’ unknown data, what is the next step? Are their probabilities assigned to my results or to each variables or is it just ‘based on my algorithm, “most likely”, this will happen.

Your tutorials are very information. Beginners like me feel lost in the jungle of academic resources while figuring out what to learn especially in the case of machine learning. Thank you for providing proper guidance.

In your opinion, once you finished a portfolio project that is well commented and structured in a Jupyter notebook, what is the best way to write a readme file to include with the notebook? What should one include in that file?

This is pure genius! I have never found any blog or website such helpful. After completing GRE and TOEFL, I am bewildered to find my area of interest. Now it feels like Machine Learning is an area I should try at least.

Thanks, Jason!
May God be with you so that you can continue doing such wonderful things.